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package com.dsideal.aiSupport.Util.DashScope;
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import com.alibaba.fastjson.JSON;
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import com.alibaba.fastjson.JSONObject;
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import com.dsideal.aiSupport.Plugin.YamlProp;
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import com.jfinal.kit.Prop;
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import lombok.SneakyThrows;
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import okhttp3.*;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import java.util.concurrent.TimeUnit;
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import static com.dsideal.aiSupport.AiSupportApplication.getEnvPrefix;
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/**
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* 阿里云达摩院人脸检测API工具类
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*/
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public class DsFaceDetect {
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private static final Logger log = LoggerFactory.getLogger(DsFaceDetect.class);
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private static final String API_URL = "https://dashscope.aliyuncs.com/api/v1/services/aigc/image2video/face-detect";
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private static final String API_KEY;
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public static Prop PropKit; // 配置文件工具
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static {
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//加载配置文件
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String configFile = "application_{?}.yaml".replace("{?}", getEnvPrefix());
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PropKit = new YamlProp(configFile);
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API_KEY = PropKit.get("aliyun.API_KEY");
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}
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/**
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* 调用人脸检测API
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*
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* @param imageUrl 图片URL
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* @param ratio 比例，例如"1:1"
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* @return 检测结果JSON对象
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* @throws Exception 异常信息
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*/
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@SneakyThrows
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public static JSONObject detectFace(String imageUrl, String ratio) {
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// 创建OkHttpClient，设置超时时间
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OkHttpClient client = new OkHttpClient().newBuilder()
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.connectTimeout(30, TimeUnit.SECONDS)
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.readTimeout(30, TimeUnit.SECONDS)
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.writeTimeout(30, TimeUnit.SECONDS)
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.build();
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// 构建请求体
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JSONObject requestBody = new JSONObject();
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requestBody.put("model", "emo-detect-v1");
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// 设置输入参数
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JSONObject input = new JSONObject();
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input.put("image_url", imageUrl);
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requestBody.put("input", input);
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// 设置其他参数
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JSONObject parameters = new JSONObject();
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parameters.put("ratio", ratio);
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requestBody.put("parameters", parameters);
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// 创建请求
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MediaType mediaType = MediaType.parse("application/json");
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RequestBody body = RequestBody.create(mediaType, requestBody.toJSONString());
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Request request = new Request.Builder()
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.url(API_URL)
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.method("POST", body)
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.addHeader("Content-Type", "application/json")
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.addHeader("Authorization", "Bearer " + API_KEY)
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.build();
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// 发送请求并获取响应
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log.info("发送人脸检测请求: {}", requestBody.toJSONString());
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Response response = client.newCall(request).execute();
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// 检查响应状态
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if (!response.isSuccessful()) {
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String errorMsg = "人脸检测API请求失败，状态码: " + response.code();
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log.error(errorMsg);
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throw new Exception(errorMsg);
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}
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// 解析响应
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String responseBody = response.body().string();
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log.info("人脸检测响应: {}", responseBody);
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return JSON.parseObject(responseBody);
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}
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/**
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* 使用示例
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*/
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@SneakyThrows
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public static void main(String[] args) {
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//EMO-detect模型，用于确认输入的人物肖像图片是否符合EMO视频生成模型的输入规范。本文档介绍了该模型提供的图像检测能力的API调用方法。
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// 图片URL
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String imageUrl = "https://dsideal.obs.cn-north-1.myhuaweicloud.com/HuangHai/BlogImages/202505131058596.png";
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// 比例
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String ratio = "1:1";
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// 调用人脸检测API
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JSONObject result = detectFace(imageUrl, ratio);
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// 处理结果
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System.out.println("检测结果: " + result.toJSONString());
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}
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}
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